Name: Troubleshooting Pipeline Errors in SAP SuccessFactors Incentive Management
Uploaded: 2020-10-15
Duration: 404 s
Description: This video describes common pipeline run errors in SAP SuccessFactors Incentive Management and how to resolve them.

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<div><div><div><div><div>This video describes common pipeline run errors in SAP SuccessFactors Incentive Management and how to resolve them.</div></div></div></div></div>

Troubleshooting Pipeline Errors in SAP SuccessFactors Incentive Management

Hello my name is Cheryl and welcome to Troubleshooting Pipeline Errors in SAP Commissions. I’ll review the following key areas to fixing pipeline errors. The Calculation tab within System Preferences and I’ll discuss what to look for in regards to the types of calculation issues, log files and best practices. Under System Preferences, the Calculation tab has two settings specific to managing warnings and errors in the Pipelines workspace. "Maximum data log entries per error" allows you to control the number of times the same error is recorded in the log. This prevents a large number of records returning the same error which create an abnormally large log file. If this field is left blank, there’s no limit to the number of errors written to the logs. "Log warnings to database" allows warning messages to be read in the Message Log workspace. When running a Pipeline, Administrators also have the option to enable Advanced Logging, which indicates how much detail is written to the logs. This is done on the Logging page of the Pipeline wizard. In general, a good practice is to leave Advanced Logging disabled unless you are troubleshooting, as it results in very large log files and slows down the pipeline process. However, If you are troubleshooting an issue and would like to enable Advanced Logging, select Yes. Performance Statistics enables you to receive advanced performance statistics and logging results. Verbose Logging gives you detailed calculation logging errors on rules and positions. You can also narrow down the results to a specific Participant, Position, Credit or Transaction, again to keep the size of the log files from getting large. SQL Logging details rule evaluations in SQL. Now, let’s look at some of the issues you may encounter when running a Pipeline.  The most common errors are: An error within Pipeline. No transactions, no deposits or credits, or values that are incorrect. Here’s how to check for an error. This is the Errors tab. One of the errors is a divide by zero value in this Incentive Rule. The rule will need to be fixed in order to fix the error. Now I’ll quickly show you the Incentive Rule that contains the error. I’ll navigate to the Attainment tab within the rule that contains the error. The Target Source is set to zero. Since the Target Source is the denominator when calculating the attainment level, leaving this at zero created a "divide by zero" error during the pipeline run. The Error tab is a key area when searching for pipeline errors because it details the errors explicitly. The Stages tab is another area to search for information regarding pipeline errors. The Allocate stage displays how many transactions and credits were processed. If no transactions are listed then the issue could be that the credit rule has filtered out all valid transactions. If you have transactions and no credits, the issue could be either the Credit Rule or, if you are using Territories the issue may be in the Classification of data or the assignment of Variables. The Reward Stage displays the same error we reviewed earlier. Notice that there are no Deposits. This is because the Quota error caused the Incentive Rule to produce no results. A zero-value Incentive Rule will not create Deposits. Next, let’s discuss log files. Log files are generated for each Pipeline Run, and are stored as text files available in the Logs tab. Multiple files are created for each stage to keep a manageable size for each file. The same quota error can also be seen in the log file for the reward stage. Let’s review troubleshooting Pipeline errors. Classification data errors may appear in the Classify Stage. Issues with allocating credits to Payees, including the results of Credit Rules may appear in the Allocate Stage. Errors with the Secondary Measurement, Incentive, and Deposit Rules may appear in the Reward Stage. Finally, the Pay stage performs only internal calculations; however, these are based on results from the Deposit Rule. If you see errors in the Pay stage, check the Deposit Rule output.  If you are using classification hierarchies and don’t see any Classification Queries in the Classify stage, make sure your classification hierarchies contain valid classification rules. If there aren’t any transactions after running in Incremental mode, verify that new and modified transactions exist for the current Period. Check the Runnable field in the transaction and make sure it’s checked. Several factors can affect Credits. If you’re preassigning transactions, first make sure that the transactions have the pre-assignment information for the correct period. Also, make sure “Credit if they are identified on the transaction” is selected in the Credit Rule. If you’re using Territories, the Transactions aren’t preassigned, make sure “Credit if they are identified on the transaction” is NOT selected in the Credit Rule. Also, ensure the Territory field is populated in the Credit Rule. If you’re using Variables, you’ll also want to make sure the right Territories are assigned to the Variable for each position for the current period. A common reason there is a lack of deposits can be found within one of the conditions in the Measurement rule. If the condition filters out valid Credits it will create a zero-value incentive, which results in zero deposits. Let’s review some Best Practices. Turn on Advanced Logging only when troubleshooting. Normal pipeline runs should never return errors. Always resolve pipeline errors. Contact the support team if you cannot resolve the pipeline error. This concludes this video. Thank you for watching.